CN115017731A - Offshore wind farm dynamic wake flow modeling method and device - Google Patents
Offshore wind farm dynamic wake flow modeling method and device Download PDFInfo
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Abstract
According to the method, the device and the storage medium for modeling the dynamic wake flow of the offshore wind farm, the running data of each fan in the whole year of the wind farm is obtained, the corresponding relation between the running state of each fan and the dynamic wake flow is determined according to the running data, the distribution plan of the fans in the wind farm is obtained, the relation between the speed and the direction of the wake flow and the sheltered area of each fan is determined based on the corresponding relation between the running state of each fan and the dynamic wake flow, the dynamic wake flow full field model of the wind farm is constructed based on the relation between the speed and the direction of the wake flow and the sheltered area of each fan, and the dynamic wake flow full field model of the offshore wind farm is corrected through simulation and field test data, so that the dynamic wake flow full field model of the target wind farm is obtained. Therefore, the relation of inter-unit wake flow dynamic distribution in the wind power plant is considered, the wind power plant can effectively control the wind power plant according to the wake flow model, wake flow distribution in the wind power plant is adjusted, active power output efficiency of the wind power plant is optimized, and maximization of the output efficiency of the wind power plant is achieved.
Description
Technical Field
The application relates to the field of wind power generation, in particular to a dynamic wake flow modeling method, a dynamic wake flow modeling device and a storage medium for an offshore wind farm.
Background
With the rapid development of the national electricity industry, an offshore wind farm is generally formed by tens or even hundreds of wind power units which are densely arranged according to a certain sequence, and has the characteristics of large scale, more units, strong wake effect, complex pneumatic coupling and the like. At present, a wind power plant control system can only realize limited domain information acquisition of a wind power plant, a unified control mode is adopted for each single machine, dynamic distribution influence of tail flow among units in the plant is ignored, interaction, group level coordination and field level coordination among fans are lacked, measurement consistency and accuracy among the fans cannot be corrected in time, safety control in the plant cannot be interlocked, and further full-field maximization of generated power cannot be realized.
Disclosure of Invention
The application provides a dynamic wake flow modeling method, device and storage medium for an offshore wind farm, which are used for solving the technical problems in the related technology.
An embodiment of a first aspect of the present application provides an offshore wind farm dynamic wake flow modeling method, including:
acquiring operation data of each fan in the whole year of the wind power plant, and determining the corresponding relation between the operation state of each fan and the dynamic wake flow according to the operation data;
acquiring a distribution plan of fans in the wind power plant, and determining the relationship between the speed and direction of wake flow and the shielding area of each fan based on the corresponding relationship between the operation state of each fan and the wake flow dynamic;
constructing a dynamic wake flow full-field model of the wind power plant based on the relation between the speed and the direction of the wake flow and the shielding area of each fan;
and correcting the offshore wind power plant dynamic wake flow full field model through simulation and field test data to obtain a target wind power plant dynamic wake flow full field model.
An embodiment of a second aspect of the present application provides an offshore wind farm dynamic wake flow modeling apparatus, including:
the first acquisition module is used for acquiring the operation data of each fan in the whole year of the wind power plant and determining the corresponding relation between the operation state of each fan and the dynamic wake flow according to the operation data;
the second acquisition module is used for acquiring a distribution plan of the fans in the wind power plant and determining the relation between the speed and the direction of the wake flow and the shielding area of each fan based on the corresponding relation between the running state of each fan and the wake flow dynamic;
the construction module is used for constructing a dynamic wake flow full-field model of the wind power plant based on the relationship between the speed and the direction of the wake flow and the shielding area of each fan;
and the correction module is used for correcting the offshore wind farm dynamic wake whole-field model through simulation and field test data to obtain a target wind farm dynamic wake whole-field model.
A computer device according to an embodiment of the third aspect of the present application is characterized by comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method according to the first aspect is implemented.
A computer storage medium according to an embodiment of a fourth aspect of the present application, wherein the computer storage medium stores computer-executable instructions; the computer executable instructions, when executed by a processor, are capable of performing the method of the first aspect as described above.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
according to the method, the device and the storage medium for modeling the dynamic wake flow of the offshore wind farm, the running data of each fan in the whole year of the wind farm is obtained, the corresponding relation between the running state of each fan and the dynamic wake flow is determined according to the running data, the distribution plan of the fans in the wind farm is obtained, the relation between the speed and the direction of the wake flow and the sheltered area of each fan is determined based on the corresponding relation between the running state of each fan and the dynamic wake flow, the dynamic wake flow full field model of the wind farm is constructed based on the relation between the speed and the direction of the wake flow and the sheltered area of each fan, and the dynamic wake flow full field model of the offshore wind farm is corrected through simulation and field test data, so that the dynamic wake flow full field model of the target wind farm is obtained. Therefore, according to the method and the device, based on the relation between the speed and the direction of the wake and the shielding area of each fan, a dynamic wake full-field model of the wind power plant is constructed, the relation of wake dynamic distribution among the units in the wind power plant is considered, the wind power plant can effectively control the wind power plants according to the wake model, the wind energy captured by each unit is further coordinated, the wake distribution in the wind power plant is adjusted, the active output efficiency of the wind power plant is optimized, and the maximization of the output efficiency of the wind power plant is realized.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow diagram of a method for modeling a dynamic wake flow of an offshore wind farm according to the present application;
FIG. 2 is a schematic structural diagram of an offshore wind farm dynamic wake flow modeling apparatus according to the present application.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The method and apparatus for modeling the dynamic wake flow of an offshore wind farm according to the embodiments of the present application will be described below with reference to the accompanying drawings.
Example one
Fig. 1 is a schematic flow chart of a dynamic wake modeling method for an offshore wind farm according to an embodiment of the present application, and as shown in fig. 1, the method may include:
In an embodiment of the application, the operation data of each fan of the wind farm in the whole year can be obtained through the SCADA database, and the operation data can include wind speed, fan power, fan rotation speed, fan yaw angle and fan pitch angle.
In an embodiment of the application, the influence of different generated powers of the fans on the wake flow velocity field is determined according to the operation data under the condition that the corresponding relation between the operation state of each fan and the dynamic wake flow needs to be analyzed, and then the quantitative relation between the wake flow velocity and the distance is expanded into the quantitative relation between the wake flow velocity and the transmission time by using the existing wake flow model (such as a Jensen model and an AV wake flow model), so that the corresponding relation between different parameters in the fan operation data and the dynamic wake flow is obtained. For example, in an embodiment of the present application, wake shapes and coverage areas in different directions corresponding to different yaw angles of a wind turbine are obtained. And in another embodiment of the application, wake flow speeds and coverage areas corresponding to different pitch angles are obtained when the fan reaches rated power.
102, obtaining a distribution plan of fans in the wind power plant, and determining the relation between the speed and the direction of wake flow and the shielding area of each fan based on the corresponding relation between the running state of each fan and the wake flow dynamic.
In an embodiment of the present application, a method for obtaining a distribution plan of fans in a wind farm, and determining a relationship between a speed and a direction of wake and a shielding area of each fan based on a correspondence between an operating state of each fan and a wake dynamic state may include: based on a distribution plan, analyzing the dynamic influence of the wake flow of the front exhaust fan on the downstream fan to obtain the relation of the dynamic distribution change of the wake flow velocity field to the generated power and fatigue of the wind turbine, further determining the relation of the velocity and direction of the wake flow to the shielding area of each fan, and calculating the effective controllable interval of the velocity and direction of the wake flow velocity field.
And, in one embodiment of the present application, analyzing the dynamic effect of the front exhaust fan wake on the downstream fan may include analyzing the effect of the front exhaust fan wake on the front end wind speed droop, wind direction skew, turbulence increase, power generation droop, and fatigue loading of the downstream fan.
103, constructing a dynamic wake flow full-field model of the wind power plant based on the relationship between the speed and the direction of the wake flow and the shielding area of each fan.
In one embodiment of the application, based on the relationship between the speed and direction of the wake and the shielding area of each fan, the wake model of the wind power plant can be constructed based on the analysis of the interaction of a plurality of serially arranged and randomly arranged wind turbines and the factors of the diameter of the fan, the distance between the fans and the incoming flow direction.
In an embodiment of the application, the method for constructing the wind farm dynamic wake full-field model based on the relationship between the speed and the direction of the wake and the sheltering area of each fan may include: and constructing a dynamic wake flow full-field model of the wind power plant based on the relation between the speed and the direction of the wake flow and the shielding area of each fan and a brake disc wake flow model algorithm.
Specifically, in one embodiment of the present application, the generalized actuator disk approach is to create a permeable disk in the flow field instead of a wind wheel, applying selected fluid micelles with momentum changes, simulating the action of the blades. When the airflow passes through the impeller, the airflow is subjected to axial resistance and tangential induction force, the tangential force and wake flow rotation effect are ignored in the actuating disc model, and the action of the impeller in the flow field is described by adopting the pressure difference formed by the axial resistance. The pressure differential across the impeller can be described by:
through conversion and derivation, the above equation can be written as:
wherein, Δ p is the front-back pressure difference of the impeller; p is a radical of - Is the impeller back pressure; p + is the impeller front pressure; rho is density; v is the incoming flow velocity; v. of - Is the impeller back speed; c T Is the thrust coefficient. C T The values are obtained from the incoming flow wind speed and thrust curves, calculated without taking into account the C due to wind shear and aerodynamic blade radial variation T The influence of (c). During calculation, the volume force source term is dynamically calculated according to the wind speed change of the front end of the wind wheel and the thrust curve. During numerical simulation, the action of the impeller on the airflow is realized by iteratively solving the momentum equation added with the volume force source item.
In one embodiment of the present application, the above-mentioned method of actuating the disc can be considered approximately as that the volume force distributed in the spanwise direction is further distributed in the tangential direction to form a disc with the volume force distributed uniformly, instead of the axial action of the rotating blades on the flow field. The actuation disc approach has lower mesh requirements and can be valuable in large scale simulations.
Further, in one embodiment of the present application, a pre-processing of the measurement data time series is required. For example, suppose the measured data at a given time k is x k ，x k The column vector comprises all data measured at the current moment, specifically the axial wind speeds of all measurement points in the three-dimensional flow field. Wherein, the simulation experiment is carried out for M times of measurement, and the time intervals of every 2 times of measurement are equal. Assume that the following linear dynamics exist for the flow field of the adjacent 2 time intervals:
x k+1 ＝Ax k
wherein, A in the above formula is a fluent full-dimensional linear state matrix.
And, in an embodiment of the present application, for a non-linear flow field, the linear model is a linear approximation to the non-linear flow field dynamics, and then stacking the measurement data accumulated M times to obtain the following 2 measurement matrices:
X＝[x 1 ,x 2 …x N-1 ]
Y＝[x 2 ,x 3 …x N ]
the full-dimensional a matrix can be calculated by the following least-squares method:
wherein the content of the first and second substances,
the dimension of the state matrix A of the full dimension is influenced by the number of state variables and has a very high order, and the measurement matrix needs to be subjected to eigenvalue decomposition to extract the main mode of the finite dimension.
In an embodiment of the present application, the method for constructing a full-field wind-turbine dynamic wake model of a wind farm to achieve order reduction of an a matrix may include the following steps:
step 1, performing r-order eigenvalue decomposition on a measurement matrix X, wherein r is a real number far smaller than the number of X rows, namely:
in the formula: Σ r is a non-negative diagonal matrix of r × r, K is an improved characteristic parameter, and the diagonal value thereof is an X characteristic value; u shape r Is a left eigenvector; v r The right eigenvectors are both right matrices.
Step 2, reducing the dimensionState matrix A r Is calculated as:
step 3, calculate A r Characteristic values of (A) and (U) r T Feature vector ω:
A r ω＝λω
step 4, the improved method corresponding to the eigenvalue λ in step 3, can be written as:
φ＝KU r ω
step 5, after the calculation is completed, the dimension reduction model can be written as:
z k+1 ＝KA r z k
in the formula: z is a radical of k For reducing dimension state variable, the original state variable x can be processed k Is obtained by dimension reduction mapping
And 6, carrying out wind power plant wake flow modeling equivalence on the model.
Aiming at the special condition of an offshore wind field, a wind power plant is equivalent to a generator, all wind turbines and wind speed models are reserved, the mechanical torque of the wind turbines is superposed, and the mechanical torque is used as the input of the equivalent generator. The equivalent parameter is calculated by the formula:
and step 104, correcting the dynamic wake flow full field model of the offshore wind farm through simulation and field test data to obtain the dynamic wake flow full field model of the target wind farm.
In an embodiment of the present application, modifying the offshore wind farm dynamic wake whole-field model through simulation and field test data includes: and (3) simulating and analyzing the wake flow dynamic by combining the generalized actuating disc theory with a CFD (computational fluid dynamics) method, and correcting the dynamic wake flow full-field model of the offshore wind farm by combining field test data.
In one embodiment of the application, the CFD method combines field anemometry data and CFD simulation calculation to evaluate wind conditions of the wind power plant, and further evaluates power generation. Specifically, CFD simulation calculation is usually performed by dividing the wind direction into at least 12 inflow wind directions according to the wind direction equiangle. The CFD simulation can be completed by adopting wind power plant flow simulation analysis and wind resource evaluation software developed based on open source OpenFOAM software.
Further, in an embodiment of the application, a wake dynamic is subjected to simulation analysis by a CFD method, and a dynamic wake full-field model of the offshore wind farm is corrected by combining field test data, so as to obtain a dynamic wake full-field model of the target wind farm.
In one embodiment of the application, a target wind power plant dynamic wake whole-field model is obtained, and then a control strategy can be obtained by using the target wind power plant dynamic wake whole-field model so as to coordinate wind energy captured by each unit, adjust wake distribution in the wind power plant and maximize output efficiency of the wind power plant.
According to the method, the device and the storage medium for modeling the dynamic wake flow of the offshore wind farm, the running data of each fan in the whole year of the wind farm is obtained, the corresponding relation between the running state of each fan and the dynamic wake flow is determined according to the running data, the distribution plan of the fans in the wind farm is obtained, the relation between the speed and the direction of the wake flow and the sheltered area of each fan is determined based on the corresponding relation between the running state of each fan and the dynamic wake flow, the dynamic wake flow full field model of the wind farm is constructed based on the relation between the speed and the direction of the wake flow and the sheltered area of each fan, and the dynamic wake flow full field model of the offshore wind farm is corrected through simulation and field test data, so that the dynamic wake flow full field model of the target wind farm is obtained. Therefore, according to the method and the device, based on the relation between the speed and the direction of the wake and the shielding area of each fan, a dynamic wake full-field model of the wind power plant is constructed, the relation of wake dynamic distribution among the units in the wind power plant is considered, the wind power plant can effectively control the wind power plants according to the wake model, the wind energy captured by each unit is further coordinated, the wake distribution in the wind power plant is adjusted, the active output efficiency of the wind power plant is optimized, and the maximization of the output efficiency of the wind power plant is realized.
Example two
Fig. 2 is a schematic structural diagram of a life prediction apparatus for an offshore wind turbine according to the present application, and as shown in fig. 2, the life prediction apparatus may include:
the first obtaining module 201 is configured to obtain operation data of each fan in the wind farm in the whole year, and determine a corresponding relationship between an operation state of each fan and a dynamic wake flow according to the operation data;
the second obtaining module 202 is configured to obtain a distribution plan of fans in the wind farm, and determine a relationship between the speed and direction of wake and a shielding area of each fan based on a corresponding relationship between the distribution plan and an operation state and wake dynamics of each fan;
the construction module 203 is used for constructing a dynamic wake flow full-field model of the wind power plant based on the relationship between the speed and the direction of the wake flow and the shielding area of each fan;
and the correcting module 204 is used for correcting the offshore wind farm dynamic wake whole-field model through simulation and field test data to obtain a target wind farm dynamic wake whole-field model.
According to the method, the device and the storage medium for modeling the dynamic wake flow of the offshore wind farm, the running data of each fan in the whole year of the wind farm is obtained, the corresponding relation between the running state of each fan and the dynamic wake flow is determined according to the running data, the distribution plan of the fans in the wind farm is obtained, the relation between the speed and the direction of the wake flow and the sheltered area of each fan is determined based on the corresponding relation between the running state of each fan and the dynamic wake flow, the dynamic wake flow full field model of the wind farm is constructed based on the relation between the speed and the direction of the wake flow and the sheltered area of each fan, and the dynamic wake flow full field model of the offshore wind farm is corrected through simulation and field test data, so that the dynamic wake flow full field model of the target wind farm is obtained. Therefore, according to the method and the device, based on the relation between the speed and the direction of the wake and the shielding area of each fan, a dynamic wake full-field model of the wind power plant is constructed, the relation of wake dynamic distribution among the units in the wind power plant is considered, the wind power plant can effectively control the wind power plants according to the wake model, the wind energy captured by each unit is further coordinated, the wake distribution in the wind power plant is adjusted, the active output efficiency of the wind power plant is optimized, and the maximization of the output efficiency of the wind power plant is realized.
In order to implement the above embodiments, the present disclosure also provides a computer device.
The computer equipment provided by the embodiment of the disclosure comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor; the processor, when executing the program, is able to implement the method as shown in fig. 1.
In order to implement the above embodiments, the present disclosure also provides a computer storage medium.
The computer storage medium provided by the embodiment of the present disclosure stores computer executable instructions; the computer-executable instructions, when executed by a processor, enable the method illustrated in fig. 1 to be implemented.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for modeling dynamic wake flow of an offshore wind farm, the method comprising:
acquiring operation data of each fan in the whole year of the wind power plant, and determining the corresponding relation between the operation state of each fan and the dynamic wake flow according to the operation data;
acquiring a distribution plan of fans in the wind power plant, and determining the relationship between the speed and direction of wake flow and the shielding area of each fan based on the corresponding relationship between the operation state of each fan and the wake flow dynamic;
constructing a dynamic wake flow full-field model of the wind power plant based on the relationship between the speed and the direction of the wake flow and the shielding area of each fan;
and correcting the offshore wind power plant dynamic wake flow full field model through simulation and field test data to obtain a target wind power plant dynamic wake flow full field model.
2. The method of claim 1, wherein the operational data comprises wind speed, wind turbine power, wind turbine speed, wind turbine yaw angle, wind turbine pitch angle.
3. The method according to claim 1, wherein the constructing a wind farm dynamic wake whole-field model based on the relationship between the speed and direction of the wake and the sheltered area of each fan comprises: and constructing a dynamic wake flow full-field model of the wind power plant based on the relation between the speed and the direction of the wake flow and the shielding area of each fan and a brake disc wake flow model algorithm.
4. The method of claim 1, wherein the modifying the offshore wind farm dynamic wake full-field model through simulation and field test data comprises: and (3) simulating and analyzing the dynamic wake flow by combining a generalized actuating disc theory with a CFD (computational fluid dynamics) method, and correcting the dynamic wake flow full-field model of the offshore wind power plant by combining field test data.
5. The method of claim 1, further comprising:
and obtaining a control strategy by using the dynamic wake flow full-field model of the target wind power plant so as to coordinate the wind energy captured by each unit, adjust the wake flow distribution in the wind power plant and realize the maximization of the output efficiency of the wind power plant.
6. An offshore wind farm dynamic wake flow modeling apparatus, the apparatus comprising:
the first acquisition module is used for acquiring the operation data of each fan in the whole year of the wind power plant and determining the corresponding relation between the operation state of each fan and the dynamic wake flow according to the operation data;
the second acquisition module is used for acquiring a distribution plan of the fans in the wind power plant and determining the relation between the speed and the direction of the wake flow and the shielding area of each fan based on the corresponding relation between the running state of each fan and the wake flow dynamic;
the construction module is used for constructing a dynamic wake flow full-field model of the wind power plant based on the relationship between the speed and the direction of the wake flow and the shielding area of each fan;
and the correction module is used for correcting the offshore wind farm dynamic wake whole-field model through simulation and field test data to obtain a target wind farm dynamic wake whole-field model.
7. The apparatus of claim 6, wherein the operational data comprises wind speed, wind turbine power, wind turbine speed, wind turbine yaw angle, wind turbine pitch angle.
8. The apparatus of claim 6, wherein the build module is further configured to:
and constructing a dynamic wake flow full-field model of the wind power plant based on the relation between the speed and the direction of the wake flow and the shielding area of each fan and a brake disc wake flow model algorithm.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method according to any one of claims 1-5 when executing the program.
10. A computer storage medium, wherein the computer storage medium stores computer-executable instructions; the computer-executable instructions, when executed by a processor, are capable of performing the method of any one of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115898788A (en) * | 2022-11-28 | 2023-04-04 | 中国华能集团清洁能源技术研究院有限公司 | Wind speed early warning diffusion type control method and system for offshore wind farm |
| CN115935645A (en) * | 2022-12-05 | 2023-04-07 | 山东大学 | Wind power plant up-regulation reserve capacity evaluation method and system based on anemometer tower data |
| CN116050287A (en) * | 2022-12-12 | 2023-05-02 | 中广核风电有限公司 | Modeling method and device for wake flow analysis of offshore floating fan |
| CN117454721A (en) * | 2023-12-21 | 2024-01-26 | 浙江远算科技有限公司 | Wind power plant wake superposition effect evaluation method and medium based on digital simulation experiment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115898788A (en) * | 2022-11-28 | 2023-04-04 | 中国华能集团清洁能源技术研究院有限公司 | Wind speed early warning diffusion type control method and system for offshore wind farm |
| CN115935645A (en) * | 2022-12-05 | 2023-04-07 | 山东大学 | Wind power plant up-regulation reserve capacity evaluation method and system based on anemometer tower data |
| CN115935645B (en) * | 2022-12-05 | 2024-05-17 | 山东大学 | Wind power plant up-regulation reserve capacity evaluation method and system based on anemometer tower data |
| CN116050287A (en) * | 2022-12-12 | 2023-05-02 | 中广核风电有限公司 | Modeling method and device for wake flow analysis of offshore floating fan |
| CN116050287B (en) * | 2022-12-12 | 2023-12-08 | 中广核风电有限公司 | Modeling method and device for wake flow analysis of offshore floating fan |
| CN117454721A (en) * | 2023-12-21 | 2024-01-26 | 浙江远算科技有限公司 | Wind power plant wake superposition effect evaluation method and medium based on digital simulation experiment |
| CN117454721B (en) * | 2023-12-21 | 2024-03-22 | 浙江远算科技有限公司 | Wind power plant wake superposition effect evaluation method and medium based on digital simulation experiment |
| CN117875221A (en) * | 2024-03-11 | 2024-04-12 | 华南理工大学 | Novel fan wake coupling method |
| CN117875221B (en) * | 2024-03-11 | 2024-05-14 | 华南理工大学 | Novel fan wake coupling method |
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